Literature DB >> 33524490

Analyze Whilst Compressing algorithm for detection of ventricular fibrillation during CPR: A comparative performance evaluation for automated external defibrillators.

Jean-Philippe Didon1, Sarah Ménétré1, Irena Jekova2, Todor Stoyanov2, Vessela Krasteva3.   

Abstract

OBJECTIVE: The aim of this study was to present new combination of algorithms for rhythm analysis during cardiopulmonary resuscitation (CPR) in automated external defibrillators (AED), called Analyze Whilst Compressing (AWC), designed for decreasing pre-shock pause and early stopping of chest compressions (CC) for treating refibrillation.
METHODS: Two stages for AED rhythm analysis were presented, namely, "Standard Analysis Stage" (conventional shock-advisory analysis run over 5 s after CC interruption every two minutes) and "AWC Stage" (two-step sequential analysis process during CPR). AWC steps were run in presence of CC (Step1), and if shockable rhythm was detected then a reconfirmation step was run in absence of CC (Step2, analysis duration 5 s).
RESULTS: In total 16,057 ECG strips from 2916 out-of-hospital cardiac arrest (OHCA) patients treated with AEDs (DEFIGARD TOUCH7, Schiller Médical, France) were subjected patient-wise to AWC training (8559 strips, 1604 patients) and validation (7498 strips, 1312 patients). Considering validation results, "Standard Analysis Stage" presented ventricular fibrillation (VF) sensitivity Se = 98.3% and non-shockable rhythm specificity Sp>99%; "AWC Stage" decision after Step2 reconfirmation achieved Se = 92.1%, Sp>99%.
CONCLUSION: AWC presented similar performances to other AED algorithms during CPR, fulfilling performance goals recommended by standards. AWC provided advances in the challenge for improving CPR quality by: (i) not interrupting chest compressions for prevalent part of non-shockable rhythms (66-83%); (ii) minimizing pre-shock pause for 92.1% of VF patients. AWC required hands-off reconfirmation in 34.4% of cases. Reconfirmation was also common limitation of other reported algorithms (25.7-100%) although following different protocols for triggering chest compression resumption and shock delivery.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Algorithm; Automated external defibrillator (AED); Cardiac arrest; Cardiopulmonary resuscitation (CPR); Chest compression; Out-of-hospital CPR; Pre-shock pause; Ventricular arrhythmia

Mesh:

Year:  2021        PMID: 33524490     DOI: 10.1016/j.resuscitation.2021.01.018

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  2 in total

Review 1.  Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review.

Authors:  Asma Alamgir; Osama Mousa; Zubair Shah
Journal:  JMIR Med Inform       Date:  2021-12-17

Review 2.  Role of artificial intelligence in defibrillators: a narrative review.

Authors:  Grace Brown; Samuel Conway; Mahmood Ahmad; Divine Adegbie; Nishil Patel; Vidushi Myneni; Mohammad Alradhawi; Niraj Kumar; Daniel R Obaid; Dominic Pimenta; Jonathan J H Bray
Journal:  Open Heart       Date:  2022-07
  2 in total

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